Why has the average time to merge merge requests doubled for enterprise customers using self-managed GitLab instances this month?

Introduction

The doubling of average merge request time for enterprise customers using self-managed GitLab instances is a critical issue that demands immediate attention. This problem directly impacts developer productivity and project timelines, potentially affecting customer satisfaction and retention. To address this complex challenge, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent system update. Has there been any significant changes to the GitLab codebase or infrastructure in the past month?

Why it matters: Recent changes could directly correlate with the performance decline. Expected answer: Yes, there was a major update to the merge request processing system. Impact on approach: If confirmed, we'd focus on rollback options and code review.

• Considering the specificity to enterprise customers, I'm wondering about scale. What's the typical volume of merge requests for these customers compared to other segments?

Why it matters: Volume differences could indicate capacity issues or bottlenecks. Expected answer: Enterprise customers process 10x more merge requests than other segments. Impact on approach: High volumes would lead us to investigate scalability and performance optimizations.

• Given the self-managed nature, I'm curious about environmental factors. Have we seen any patterns in terms of hardware specifications or configurations among affected customers?

Why it matters: Environmental factors could explain performance variances. Expected answer: No clear pattern in hardware specs, but all affected instances are running on-premises. Impact on approach: We'd need to investigate potential interactions between GitLab and various on-premises setups.

• Thinking about potential data anomalies, has there been any change in how we measure or define "time to merge" for merge requests?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes to the metric definition or measurement process. Impact on approach: Confirms the issue is with actual performance, not data collection.